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At least 199 records · Page 11

[Micron]ADS-B Detect and Avoid Flight Tests on Phantom 4 Unmanned Aircraft System

Researchers at the National Aeronautics and Space Administration Armstrong Flight Research Center in Edwards, California and Vigilant Aerospace Systems collaborated for the flight-test demonstration of an Automatic Dependent Surveillance-Broadcast based collision avoidance technology on a small unmanned aircraft system equipped with the uAvionix Automatic Dependent Surveillance-Broadcast transponder. The purpose of the testing was to demonstrate that National Aeronautics and Space Administration / Vigilant software and algorithms, commercialized as the FlightHorizon UAS"TM", are compatible with uAvionix hardware systems and the DJI Phantom 4 small unmanned aircraft system. The testing and demonstrations were necessary for both parties to further develop and certify the technology in three key areas: flights beyond visual line of sight, collision avoidance, and autonomous operations. The National Aeronautics and Space Administration and Vigilant Aerospace Systems have developed and successfully flight-tested an Automatic Dependent Surveillance-Broadcast Detect and Avoid system on the Phantom 4 small unmanned aircraft system. The Automatic Dependent Surveillance-Broadcast Detect and Avoid system architecture is especially suited for small unmanned aircraft systems because it integrates: 1) miniaturized Automatic Dependent Surveillance-Broadcast hardware; 2) radio data-link communications; 3) software algorithms for real-time Automatic Dependent Surveillance-Broadcast data integration, conflict detection, and alerting; and 4) a synthetic vision display using a fully-integrated National Aeronautics and Space Administration geobrowser for three dimensional graphical representations for ownship and air traffic situational awareness. The flight-test objectives were to evaluate the performance of Automatic Dependent Surveillance-Broadcast Detect and Avoid collision avoidance technology as installed on two small unmanned aircraft systems. In December 2016, four flight tests were conducted at Edwards Air Force Base. Researchers in the ground control station looking at displays were able to verify the Automatic Dependent Surveillance-Broadcast target detection and collision avoidance resolutions.

avoidance↗

Integration of Automated Systems (IAS) Flight Test - Hazard Perception & Avoidance (HPA) Results

The Integration of Automated Systems (IAS) flight test series concluded in October 2023 in support of NASA's Advanced Air Mobility (AAM) project. These flights include crewed, test (i.e., ownship) and traffic (i.e., intruder) aircraft that flew with unique technologies onboard. The presentation includes overviews of the flight tet itself and the specific results that pertain to the Hazard Perception and Avoidance (HPA) technical areas. HPA tested the FAA's Airborne Collision Avoidance System X (ACAS X), a next-generation collision avoidance tool developed to support different aircraft types and operations. The rotorcraft variant, ACAS Xr, is designed to accommodate existing helicopter platforms and in-development, vertical takeoff and landing (VTOL) concepts, which are critical to the emerging AAM concept of operations. Two configurations of ACAS Xr were examined: Collision Avoidance System (CAS, similar to the Traffic Collision Avoidance System [TCAS] II) and Detect and Avoid (DAA, previously developed to provide added situational awareness for remote pilots). Additionally, this system was flown in cruise and low-speed flight regimes as well as within en-route and (emulated), structured (i.e., dense/urban), and terminal airspaces. Results include the types of alerts generated by ACAS Xr across the different configurations, the distances at which the alerts were generated, response times, manuever sizes, miss distances, and general comments from pilots. Key takeaways and next steps are also provided.

detect and avoid↗

Advanced Air Mobility Operations & Automation Part II Technical Lecture

The Airborne Collision Avoidance System X (ACAS X) is a next-generation collision avoidance tool developed to support different aircraft types and operations. The rotorcraft variant – referred to as ACAS XR – is designed to accommodate existing helicopter platforms as well as in-development, electric vertical takeoff and landing concepts, which are critical to the emerging concept of operations referred to as Advanced Air Mobility. The fundamental role of ACAS XR is to provide Detect and Avoid (DAA) and/or Collision Avoidance (CA) protection against airborne traffic. DAA alerting and guidance in the context of ACAS XR is caution-level and “suggestive,” and is to be used by the pilot if, and when, they decide to maneuver against an identified threat to DAA “well clear.” The CA alerting, by contrast, is warning-level and “directive,” with the pilot required to comply with the associated guidance to prevent a predicted Near Midair Collision (NMAC). The CA alerts generated by ACAS XR are referred to as Resolution Advisories (RAs) consistent with previous CA systems. Unlike earlier CA systems, ACAS XR issues RAs in the horizontal and vertical dimensions as well as multi-axis RAs (referred to as “Blended” RAs). According to the Minimal Operational Performance Standards of DAA systems for Unmanned Aircraft Systems, maneuvers to comply with RAs may be automated, whereas maneuvers based on DAA alerting assume a manual response. The current presentation discusses two human-in-the-loop simulations that presented rotorcraft pilots with ACAS XR alerts and guidance in eVTOL simulators with varying levels of automation. It also presents overviews of these studies as well as how they assisted live flight tests, which will occur throughout 2023.

air taxis↗

Safe Space Conduct: NASA Best Practices Overview

While prevention of launch and on-orbit collisions has been an institutional concern of NASA for several decades (beginning with the Shuttle program), historically the paucity of spaceactors and deployed payloads made the conduct of such protection activities relatively straightforward. With the substantial increases in launched payloads over the last several years, collision avoidance operations have become substantially more complicated. At the same time, many operators are uncertain regarding what collision avoidance activities are appropriate to their missions. The lack of a space traffic management authority to articulate standards and guidelines for such conduct has only increased the confusion.In response to this situation, NASA has published a Spacecraft Conjunction Assessment and Collision Avoidance Handbook, which articulates and explains the launch and on-orbit collision avoidance best practices that the Agency has developed and is requiring of present and future NASA missions. Because the CA2 Handbook is a living document regularly updated to reflect best practices changes as the industry develops, feedback from both NASA missions and other users is continuously collected in order to issue CA2 Handbook updates.This talk will summarize and explain the collision avoidance best practices from the CA2Handbook, along with the key issues that drove the selection of those practices.

Conjunction Assessment↗

NASA Best Practices Overview

While prevention of launch and on-orbit collisions has been an institutional concern of NASA for several decades (beginning with the Shuttle program), historically the paucity of space actors and deployed payloads made the conduct of such protection activities relatively straightforward. With the substantial increases in launched payloads over the last several years, collision avoidance operations have become substantially more complicated. At the same time, many operators are uncertain regarding what collision avoidance activities are appropriate to their missions. The lack of a space traffic management authority to articulate standards and guidelines for such conduct has only increased the confusion. In response to this situation, NASA has published a Spacecraft Conjunction Assessment and Collision Avoidance Handbook, which articulates and explains the launch and on-orbit collision avoidance best practices that the Agency has developed and is requiring of present and future NASA missions. Because the CA2 Handbook is a living document regularly updated to reflect best practices changes as the industry develops, feedback from both NASA missions and other users is continuously collected in order to issue CA2 Handbook updates. This talk will summarize and explain the collision avoidance best practices from the CA2 Handbook, along with the key issues that drove the selection of those practices.

Conjunction Assessment↗

Integration of Automated Systems (IAS) Flight Test Overview

The Integration of Automated Systems (IAS) Project is conducting a series of 2023 flight tests supporting NASA's Advanced Air Mobility (AAM) and National Campaign efforts. These flights include crewed, test (i.e., ownship) and traffic (i.e., intruder) aircraft that will fly with unique technologies onboard. The presentation will include overviews of the Hazard Perception and Avoidance (HPA) and Flight Path Management (FPM) technical areas but will focus primarily on HPA. HPA will test the FAA's Airborne Collision Avoidance System X (ACAS X), a next-generation collision avoidance tool developed to support different aircraft types and operations. The rotorcraft variant, ACAS Xr, is designed to accommodate existing helicopter platforms and in-development, vertical takeoff and landing (VTOL) concepts, which are critical to the emerging AAM concept of operations. Two configurations of ACAS Xr will be examined: Collision Avoidance System (CAS, similar to the Traffic Collision Avoidance System [TCAS] II) and Detect and Avoid (DAA, previously developed to provide added situational awareness for uncrewed aircraft). Additionally, this system will be explored during cruise and low-speed flight as well as flights within en-route, structured (i.e., dense/urban), and terminal airspaces. Scripted flight conflicts will be conducted, and these conflicts will be mitigated through maneuvers that are manual (i.e., performed by the pilots) or automated (i.e., achieved by the cooperation of the program middleware and onboard ownship systems). Objective data will be collected involving system and pilot performance as well as pilot decisions; subjective data will include pilot opinions of ACAS Xr's alerting and guidance as well as the automated maneuvers.

detect and avoid↗

FT-01: Autonomous Helicopter Flight Testing Over Long Island Sound Special Session - Hazard Perception and Avoidance Tech Area

This presentation is included as part of a panel reporting on the Integration of Automated Systems (IAS) flight test series. The IAS series concluded in October 2023 and was conducted under NASA’s Advanced Air Mobility project and in partnership with Sikorsky and the Defense Advanced Research Projects Agency (DARPA). The flight test effort included two crewed rotorcraft platforms. The first, a modified S-76B helicopter, served as the “ownship” for the duration of the flight test. The second vehicle, a modified S-70, served as the intruder aircraft. One Sikorsky pilot and one NASA test pilot was onboard each aircraft for every test point, with the NASA test pilot responsible for interacting with the research systems under test. This portion of the panel presentation focuses on the results of the flight test that assessed the Federal Aviation Administration’s (FAA) next-generation collision avoidance system, the Airborne Collision Avoidance System X for Rotorcraft (ACAS Xr). The two configurations available within ACAS Xr – the Collision Avoidance System (CAS) configuration and the Detect and Avoid (DAA) configuration – were flown with an onboard pilot under Visual Flight Rules in controlled airspace over the Long Island Sound (Connecticut, USA). A total of 33 flight test cards were flown with ACAS Xr active. Results showed that the ACAS Xr alerting and guidance was largely effective and rated positively by the NASA test pilots, exemplified by zero instances of the pilots overriding an ACAS Xr Resolution Advisory (RA). Key areas of improvement, however, were noted, particularly with regards to the lack of an aural alert indicating a need to accelerate when receiving an RA at low speed and the occurrence of multiple RAs that the pilots found to be unacceptable.

detect and avoid↗

TDD LoRa and Delta Encoding in Low-Power Networks of Environmental Sensor Arrays for Temperature and Deformation Monitoring

Abstract Densely distributed sensor networks can revolutionize environmental observations by providing real-time data with an unprecedented spatiotemporal resolution. However, field deployments often pose unique challenges in terms of power provisions and wireless connectivity. We present a framework for wirelessly connected distributed sensor arrays for near-surface temperature and/or deformation monitoring. Our research focuses on a novel time division duplex implementation of the LoRa protocol, enabling battery powered base stations and avoiding collisions within the network. In order to minimize transmissions and improve battery life throughout the network, we propose a dedicated delta encoding algorithm that utilizes the spatial and temporal similarity in the acquired data sets. We implemented the developed technologies in a AA battery powered hardware platform that can be used as a wireless data logger or base station, and we conducted an assessment of the power consumption. Without data compression, the projected battery life for a data logger is 4.74 years, and a wireless base stations can last several weeks or months depending on the amount of network traffic. The delta encoding algorithm can further improve this battery life with a factor of up to 3.50. Our results demonstrate the viability of the proposed methods for low-power environmental wireless sensor networks.

54 ENVIRONMENTAL SCIENCES↗

Assessment of pilot workload with the introduction of an airborne threat-alert system

Simulated line operations were used to assess the value of the TCAS on the pilot's ability to avoid a collision and to determine the effects of various display configurations and information contents on the flight-crew performance and workload. The crew flew a Phase II Link/Boeing 727 simulator in a simulated ATC environment. Four levels of collision avoidance information were evaluated using the following TCAS display formats: no TCAS information, TCAS information with no traffic display information, TCAS information with threat-activated traffic display information, and TCAS information with a full-time traffic display of threat information. It was found that the use of a threat-activated TCAS display significantly reduced the first officers' workload was significantly reduced by the threat-activated TCAS display, as were the workloads of the captain and the second officer.

Battiste, Vernol↗

Step 1: Human System Integration Simulation and Flight Test Progress Report

The Access 5 Human Systems Integration Work Package produced simulation and flight demonstration planning products for use throughout the program. These included: Test Objectives for Command, Control, Communications; Pilot Questionnaire for Command, Control, Communications; Air Traffic Controller Questionnaire for Command, Control, Communications; Test Objectives for Collision Avoidance; Pilot Questionnaire for Collision Avoidance; Plans for Unmanned Aircraft Systems Control Station Simulations Flight Requirements for the Airspace Operations Demonstration

Source record↗

The International Space Station and the Space Debris Environment: 10 Years On

For just over a decade the International Space Station (ISS), the most heavily protected vehicle in Earth orbit, has weathered the space debris environment well. Numerous hypervelocity impact features on the surface of ISS caused by small orbital debris and meteoroids have been observed. In addition to typical impacts seen on the large solar arrays, craters have been discovered on windows, hand rails, thermal blankets, radiators, and even a visiting logistics module. None of these impacts have resulted in any degradation of the operation or mission of the ISS. Validating the rate of small particle impacts on the ISS as predicted by space debris environment models is extremely complex. First, the ISS has been an evolving structure, from its original 20 metric tons to nearly 300 metric tons (excluding logistics vehicles) ten years later. Hence, the anticipated space debris impact rate has grown with the increasing size of ISS. Secondly, a comprehensive visual or photographic examination of the complete exterior of ISS has never been accomplished. In fact, most impact features have been discovered serendipitously. Further complications include the estimation of the size of an impacting particle without knowing its mass, velocity, and angle of impact and the effect of shadowing by some ISS components. Inadvertently and deliberately, the ISS has also been the source of space debris. The U.S. Space Surveillance Network officially cataloged 65 debris from ISS from November 1998 to November 2008: from lost cameras, sockets, and tool bags to intentionally discarded equipment and an old space suit. Fortunately, the majority of these objects fall back to Earth quickly with an average orbital lifetime of less than two months and a maximum orbital lifetime of a little more than 15 months. The cumulative total number of debris object-years is almost exactly 10, the equivalent of one piece of debris remaining in orbit for 10 years. An unknown number of debris too small to be tracked and cataloged have also been generated, but normally with even shorter orbital lifetimes. Finally, eight collision avoidance maneuvers have been performed to avoid potential collisions between ISS and large, tracked space debris. The most recent such maneuver was accomplished by ESA's Automated Transfer Vehicle, the Jules Verne, just three months before the 10th anniversary of the launch of ISS's first element.

Johnson, Nicholas↗

Magnetically Attached Multifunction Maintenance Rover

A versatile mobile telerobot, denoted the magnetically attached multifunction maintenance rover (MAGMER), has been proposed for use in the inspection and maintenance of the surfaces of ships, tanks containing petrochemicals, and other large ferromagnetic structures. As its name suggests, this robot would utilize magnetic attraction to adhere to a structure. As it moved along the surface of the structure, the MAGMER would perform tasks that could include close-up visual inspection by use of video cameras, various sensors, and/or removal of paint by water-jet blasting, laser heating, or induction heating. The water-jet nozzles would be mounted coaxially within compressed-air-powered venturi nozzles that would collect the paint debris dislodged by the jets. The MAGMER would be deployed, powered, and controlled from a truck, to which it would be connected by hoses for water, compressed air, and collection of debris and by cables for electric power and communication (see Figure 1). The operation of the MAGMER on a typical large structure would necessitate the use of long cables and hoses, which can be heavy. To reduce the load of the hoses and cables on the MAGMER and thereby ensure its ability to adhere to vertical and overhanging surfaces, the hoses and cables would be paid out through telescopic booms that would be parts of a MAGMER support system. The MAGMER would move by use of four motorized, steerable wheels, each of which would be mounted in an assembly that would include permanent magnets and four pole pieces (see Figure 2). The wheels would protrude from between the pole pieces by only about 3 mm, so that the gap between the pole pieces and the ferromagnetic surface would be just large enough to permit motion along the surface but not so large as to reduce the magnetic attraction excessively. In addition to the wheel assemblies, the MAGMER would include magnetic adherence enhancement fixtures, which would comprise arrays of permanent magnets and pole pieces that could be adjusted to maximize or minimize the overall attractive magnetic force. Even with a paint thickness of 2 mm, a preliminary design provides a safety factor of 5 in the magnetic force in the upside- down, water-jets-operating condition, in which the total load (including the weight of the MAGMER and cables and the water-jet force) would be about 260 lb (the weight of 118 kg). Optionally, the MAGMER could carry magnetic shielding and/or could be equipped with a demagnetizing module to remove residual magnetism from the structure. The MAGMER would carry four charge-coupled-device cameras for visual inspection, monitoring of operation, navigation, and avoidance of collisions with obstacles. The control system of the MAGMER would include navigation and collision-avoidance subsystems that would utilize surface features as landmarks, in addition to direct images of obstacles.

Bar-Cohen, Yoseph↗

Analytical Assessment of Simultaneous Parallel Approach Feasibility from Total System Error

In a simultaneous paired approach to closely-spaced parallel runways, a pair of aircraft flies in close proximity on parallel approach paths. The aircraft pair must maintain a longitudinal separation within a range that avoids wake encounters and, if one of the aircraft blunders, avoids collision. Wake avoidance defines the rear gate of the longitudinal separation. The lead aircraft generates a wake vortex that, with the aid of crosswinds, can travel laterally onto the path of the trail aircraft. As runway separation decreases, the wake has less distance to traverse to reach the path of the trail aircraft. The total system error of each aircraft further reduces this distance. The total system error is often modeled as a probability distribution function. Therefore, Monte-Carlo simulations are a favored tool for assessing a "safe" rear-gate. However, safety for paired approaches typically requires that a catastrophic wake encounter be a rare one-in-a-billion event during normal operation. Using a Monte-Carlo simulation to assert this event rarity with confidence requires a massive number of runs. Such large runs do not lend themselves to rapid turn-around during the early stages of investigation when the goal is to eliminate the infeasible regions of the solution space and to perform trades among the independent variables in the operational concept. One can employ statistical analysis using simplified models more efficiently to narrow the solution space and identify promising trades for more in-depth investigation using Monte-Carlo simulations. These simple, analytical models not only have to address the uncertainty of the total system error but also the uncertainty in navigation sources used to alert an abort of the procedure. This paper presents a method for integrating total system error, procedure abort rates, avionics failures, and surveillance errors into a statistical analysis that identifies the likely feasible runway separations for simultaneous paired approaches.

Madden, Michael M.↗

Airport Traffic Conflict Detection and Resolution Algorithm Evaluation

Two conflict detection and resolution (CD&R) algorithms for the terminal maneuvering area (TMA) were evaluated in a fast-time batch simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center. One CD&R algorithm, developed at NASA, was designed to enhance surface situation awareness and provide cockpit alerts of potential conflicts during runway, taxi, and low altitude air-to-air operations. The second algorithm, Enhanced Traffic Situation Awareness on the Airport Surface with Indications and Alerts (SURF IA), was designed to increase flight crew awareness of the runway environment and facilitate an appropriate and timely response to potential conflict situations. The purpose of the study was to evaluate the performance of the aircraft-based CD&R algorithms during various runway, taxiway, and low altitude scenarios, multiple levels of CD&R system equipage, and various levels of horizontal position accuracy. Algorithm performance was assessed through various metrics including the collision rate, nuisance and missed alert rate, and alert toggling rate. The data suggests that, in general, alert toggling, nuisance and missed alerts, and unnecessary maneuvering occurred more frequently as the position accuracy was reduced. Collision avoidance was more effective when all of the aircraft were equipped with CD&R and maneuvered to avoid a collision after an alert was issued. In order to reduce the number of unwanted (nuisance) alerts when taxiing across a runway, a buffer is needed between the hold line and the alerting zone so alerts are not generated when an aircraft is behind the hold line. All of the results support RTCA horizontal position accuracy requirements for performing a CD&R function to reduce the likelihood and severity of runway incursions and collisions.

Jones, Denise R.↗

Space Traffic Management with a NASA UAS Traffic Management (UTM) Inspired Architecture

Space is becoming increasingly congested as the number of on-orbit satellites and debris objects continues to grow. Space traffic management (STM) is critical for ensuring that the expanding orbital population operates safely and efficiently, avoiding collisions and radio-frequency interference while still facilitating widespread space operations. Recent events such as the FCC approval of SpaceX’s ~12,000 satellite constellation, the signing of Space Policy Directive 3 (which moves Space Situational Awareness responsibilities away from the Department of Defense and to a civil agency), and the growth in rideshare and small launch vehicles illustrate the rapidly changing nature of this domain. This paper will describe the concept of operations (ConOps) for a civilian STM research initiative, which has been developed from previous NASA work to enable safe operation of small unmanned aircraft systems. The STM ConOps proposes an architecture to enable efficient data sharing and coordination between participants to facilitate safe spaceflight operations. It is designed to utilize and promote the emerging field of commercial STM services, as a complement to existing government-provided STM services. The concept envisions a phased evolution that would gradually integrate additional capabilities, proposing a first phase architecture and tentative plans for a broader system. Work towards developing an STM research and prototyping platform is also discussed.

UTM↗

The NASA Urban Air Mobility Testbed Flight Research Aircraft

The National Aeronautics and Space Administration (NASA) is leading government, industry and academic research effort known as Urban Air Mobility (UAM). The UAM activity goal is to develop the technology needed to make possible an urban air transportation system that makes use of human-crewed and crewless vehicles using automation, artificial intelligence and other technologies to safely and efficiently air transport people and goods within an urban environment. The NASA Langley Research Center (LaRC) created a UAM Flight Research Testbed Aircraft from a Cessna LC40 general aviation aircraft. The testbed has updated digital avionics and research systems needed to conduct flight research. The aircraft has two separate autopilots; a standard Federal Aviation Ad-ministration (FAA) certified system, and a modified research autopilot. The research autopilot has modifications that allow increased authority and enhancements to allow more automation and artificial intelligence controls. A network of three research computers hosts software to research several activities including automated air traffic sense and avoid, ground collision avoidance and obstacle avoidance. These UAM research activities involve automation and artificial intelligence technologies developed at three NASA centers. The NASA Langley, NASA Armstrong, and NASA Ames Research Centers are working together to develop and test these UAM technologies. This paper provides details of the systems, capabilities and research projects of the UAM Testbed Research Aircraft.

Howell, Charles T.↗

Sense-and-Avoid Equivalent Level of Safety Definition for Unmanned Aircraft Systems. Revision 9

Since unmanned aircraft do not have a pilot on-board the aircraft, they cannot literally comply with the "see and avoid" requirement beyond a short distance from the location of the unmanned pilot. No performance standards are presently defined for unmanned Sense and Avoid systems, and the FAA has no published approval criteria for a collision avoidance system. Before the FAA can develop the necessary guidance (rules / regulations / policy) regarding the see-and-avoid requirements for Unmanned Aircraft Systems (UAS), a concise understanding of the term "equivalent level of safety" must be attained. Since this term is open to interpretation, the UAS industry and FAA need to come to an agreement on how this term can be defined and applied for a safe and acceptable collision avoidance capability for unmanned aircraft. Defining an equivalent level of safety (ELOS) for sense and avoid is one of the first steps in understanding the requirement and developing a collision avoidance capability. This document provides a functional level definition of see-and-avoid as it applies to unmanned aircraft. The sense and avoid ELOS definition is intended as a bridge between the see and avoid requirement and the system level requirements for unmanned aircraft sense and avoid systems. Sense and avoid ELOS is defined in a rather abstract way, meaning that it is not technology or system specific, and the definition provides key parameters (and a context for those parameters) to focus the development of cooperative and non-cooperative sense and avoid system requirements.

Source record↗

Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning

Finding the most likely path to a set of failure states is important to the analysis of safety-critical systems that operate over a sequence of time steps, such as aircraft collision avoidance systems and autonomous cars. In many applications such as autonomous driving, failures cannot be completely eliminated due to the complex stochastic environment in which the system operates.As a result, safety validation is not only concerned about whether a failure can occur, but also discovering which failures are most likely to occur. This article presents adaptive stress testing (AST), a framework for finding the most likely path to a failure event in simulation. We consider a general black box setting for partially observable and continuous-valued systems operating in an environment with stochastic disturbances. We formulate the problem as a Markov decision process and use reinforcement learning to optimize it. The approach is simulation-based and does not require internal knowledge of the system, making it suitable for black-box testing of large systems. We present different formulations depending on whether the state is fully observable or partially observable. In the latter case, we present a modified Monte Carlo tree search algorithm that only requires access to the pseudorandom number generator of the simulator to overcome partial observability. We also present an extension of the framework, called differential adaptive stress testing (DAST), that can find failures that occur in one system but not in another. This type of differential analysis is useful in applications such as regression testing, where we are concerned with finding areas of relative weakness compared to a baseline. We demonstrate the effectiveness of the approach on an aircraft collision avoidance application, where a prototype aircraft collision avoidance system is stress tested to find the most likely scenarios of near mid-air collision.

Verification and Validation↗